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- 144 creator axel-cyrille-ngonga-ngomo.
- 144 creator christina-unger.
- 144 creator lorenz-buehmann.
- 144 creator ricardo-usbeck.
- 144 type InProceedings.
- 144 label "HAWK - Hybrid Question Answering using Linked Data".
- 144 sameAs 144.
- 144 abstract "The decentral architecture behind the Web has led to pieces of information being distributed across data sources with varying structure. Hence, answering complex questions often required combining information from structured and unstructured data sources. We present HAWK, a novel entity search approach for Hybrid Question Answering based on combining Linked Data and textual data. The approach uses predicate-argument representations of questions to derive equivalent combinations of SPARQL query fragments and text queries. These are executed so as to integrate the results of the text queries into SPARQL and thus generate a formal interpretation of the query. We present a thorough evaluation of the framework, including an analysis of the influence of entity annotation tools on the generation process of the hybrid queries and a study of the overall accuracy of the system. Our results show that HAWK 0.68 respectively 0.61 F-measure within the training respectively test phases on the Question Answering over Linked Data (QALD-4) hybrid query benchmark.".
- 144 hasAuthorList authorList.
- 144 isPartOf proceedings.
- 144 keyword "Entity Search".
- 144 keyword "Hybrid Question Answering".
- 144 keyword "Ranking".
- 144 title "HAWK - Hybrid Question Answering using Linked Data".